calcSeCox: Computation of standard errors for predictions

In bozenne/riskRegressionLight: Light version of the package riskRegression

Description

Compute the standard error associated to the predictions from Cox regression model using a first order von Mises expansion of the functional (cumulative hazard or survival).

Usage

calcSeCox(object, times, nTimes, type, diag, Lambda0, object.n,
  object.time, object.eXb, object.strata, nStrata, new.n, new.eXb,
  new.LPdata, new.strata, new.survival, nVar, export, store.iid)

Arguments

object	The fitted Cox regression model object either obtained with coxph (survival package) or cph (rms package).
times	Vector of times at which to return the estimated hazard/survival.
nTimes	the length of the argument times.
type	One or several strings that match (either in lower or upper case or mixtures) one or several of the strings "hazard","cumhazard", "survival".
diag	[logical] If TRUE only compute the hazard/cumlative hazard/survival for the i-th row in dataset at the i-th time.
Lambda0	the baseline hazard estimate returned by BaseHazStrata_cpp.
object.n	the number of observations in the dataset used to estimate the object.
object.time	the time to event of the observations used to estimate the object.
object.eXb	the exponential of the linear predictor relative to the observations used to estimate the object.
object.strata	the strata index of the observations used to estimate the object.
nStrata	the number of strata.
new.n	the number of observations for which the prediction was performed.
new.eXb	the linear predictor evaluated for the new observations.
new.LPdata	the variables involved in the linear predictor for the new observations.
new.strata	the strata indicator for the new observations.
new.survival	the survival evaluated for the new observations.
nVar	the number of variables that form the linear predictor.
export	can be "iid" to return the value of the influence function for each observation. "se" to return the standard error for a given timepoint.
store.iid	Implementation used to estimate the influence function and the standard error. Can be "full" or "minimal". See the details section.

Details

Can also return the estimated influence function for the cumulative hazard function and survival probabilities the sum over the observations of the estimated influence function.

store.iid="full" compute the influence function for each observation at each time in the argument times before computing the standard error / influence functions. store.iid="minimal" recompute for each subject specific prediction the influence function for the baseline hazard. This avoid to store all the influence functions but may lead to repeated evaluation of the influence function. This solution is therefore more efficient in memory usage but may not be in terms of computation time.

Value

A list optionally containing the standard error for the survival, cumulative hazard and hazard.

Author(s)

Brice Ozenne [e-mail], Thomas A. Gerds [e-mail]

bozenne/riskRegressionLight documentation built on May 7, 2019, 12:52 a.m.